CN106030655A - Articulated structure registration in magnetic resonance images of the brain - Google Patents
Articulated structure registration in magnetic resonance images of the brain Download PDFInfo
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Abstract
A registration processor (74) is configured to obtain articulated brain substructures using acquired brain image data and template brain image data. The registration processor (74) annotates the brain image data; registers the brain image data with template image data using global brain registration; and registers at least one brain structure of the brain image data a corresponding brain structure of the template image data using a local brain sub-structure registration. The registration processor (74) articulates articulated substructures of the registered brain structures to improve registration using articulated substructure registration.
Description
Background technology
Alzheimer disease and other kinds of dementia are the symptoms of health decline, affect millions of people.To such
The early stage detection of the outbreak of symptom can promote early intervention and improve patient health, quality of life and general effect.These
Symptom is relevant with the atrophy in the hippocampus district of brain.
The registration of brain magnetic resonance (MR) volume is the basic operation for processing brain information.This information is used for swelling brain
Tumor, the brain development of child, apoplexy are disposed and the diagnosis of neurodegenerative diseases.One brain is (pending to carry out the mesh diagnosed
Mark brain) allow clinicist to compare with the registration of another brain (template comprising the Given information about its structure or atlas brain)
The shape of the voxel one by one between target brain and template brain and strength information.To the shape between target brain and template brain/
The identification of strength difference and quantization allow clinicist automatically or semi-automatically to generate the feature for brain diagnosis.
The method being currently used in brain registration is divided into: (i) global registration and (ii) local registration.In global registration method
In, by (barycenter) translation and the combination of rotation, such as by affine transformation, whole target brain is registrated to template brain.?
In local registration, each voxel in target brain is transformed to shape and the strength characteristic of matching template brain voxel.
These currently known methods presented above propose (is such as imitated by the global registration in calculating anatomy
Penetrate conversion) or local registration or combination of the two carry out the registration to 2D/3D region/object.But, these registration sides
Method is not incorporated to process the object structure information of global or local registration.
Summary of the invention
According to an embodiment, a kind of brain registration arrangement, including: having the registration processor of processor, it is configured to:
Brain image data is annotated；Overall situation brain registration is used to be registrated with template image data by brain image data；Use
Local cerebral minor structure registration is by the corresponding brain structure of at least one brain structure registration of brain image data to template image data；
And it is hinged to improve to use hinged (articulated) minor structure registration to carry out the hinged minor structure of the brain structure being registered
Registration.
According to a kind of method, a kind of method for brain registration, including: brain image data is annotated；Use the overall situation
Brain image data is registrated by brain registration with template image data；Local cerebral minor structure is used to registrate brain image data
At least one brain structure registration is to the corresponding brain structure of template image data；And use hinged minor structure registration to being registered
The hinged minor structure of brain structure carries out hinged to improve registration.
According to another embodiment, a kind of brain registration arrangement, including: annotations module, it is for carrying out brain image data
Annotation；Global registration module, it is used for using full brain registration to be registrated with template image data by brain image data；Local is joined
Quasi-mode block, it is for using local cerebral minor structure registration by least one brain structure registration of brain image data to template image number
According to corresponding brain structure；And hinge module, it is for using the hinged minor structure registration hinged son to the brain structure being registered
Structure carries out hinged to improve registration.
One advantage is the overlapping of increase between Typical AVM with template brain.
Another advantage is the bridge joint between global and local brain method for registering.
Accompanying drawing explanation
By reading and understanding detailed description below, the further advantage of the present invention is for ordinary skill people
Will be apparent from for Yuan.
Fig. 1 depicts the MRI system for the registration of articulated structure in the magnetic resonance image (MRI) of brain.
Fig. 2 depicts the method for the registration of articulated structure in the magnetic resonance image (MRI) of brain；
Fig. 3 depicts the annotated brain structure being superimposed upon on cerebral tissue.
Fig. 4 depicts the hippocampus target being registered to formwork structure.
Fig. 5 depicts the detailed method registrated for hinged minor structure.
Fig. 6 depicts the figure of the structure about junction surface.
Specific embodiment
This application provides the method worked between global and local registrates.The application provides for by one group of hinged son
The registration of the brain structure of representation.This such as hippocampus, thalamus and the anatomy of skull of will being made up of one group of minor structure
Take into account with functional brain structure.The shape of these minor structures, attitude and intensity are different with the difference of brain, even and if
Also it is different between the different brain hemisphere of same brain.Each brain structure is strong by rigid shape and the surface that is associated thereof
Angle value describes, and it is as hinged to deforming that way.This hinged deformation describes and connects about similar with mechanical hinge
One group of rotation of contact.Each minor structure can also be broken down into less subassembly so that registration is the most accurate.
With reference to Fig. 1, magnetic resonance (MR) imaging system 10 utilizes MR to come the area-of-interest (ROI) to patient 12, i.e. brain, enters
Row imaging.System 10 includes scanning device 14, and scanning device 14 limits the imaging volume 16 being suitably sized to accommodate ROI and (refers to body film
Show).Patient support can be used patient 12 to be supported in scanning device 14 and promote in imaging volume 16, ROI to be carried out
Location.
Scanning device 14 includes that main magnet 18, main magnet 18 produce strong, the quiet B extended through imaging volume 160Magnetic field.Main
Magnet 18 generally uses superconducting coil to produce quiet B0Magnetic field.But, main magnet 18 can also use permanent magnet or impedance magnet.
In the case of using superconducting coil, main magnet 18 includes the cooling system for superconducting coil, the such as low temperature of liquid helium cooling
Thermostat.Quiet B in imaging volume 160The intensity in magnetic field be typically following in one: 0.23 tesla, 0.5 tesla, 1.5
Tesla, 3 teslas, 7 teslas etc., but other intensity are also expected.
Control the gradient controller 20 of scanning device 14 to use multiple magnetic field gradient coils 22 of scanning device 14 by magnetic field ladder
Degree, such as x, y and z gradient, it is superimposed upon the quiet B of imaging volume 160On magnetic field.Magnetic field gradient is to the magnetic spin in imaging volume 16
It is spatially encoded.Generally, multiple magnetic field gradient coils 22 are included on three orthogonal intersection space directions three be spatially encoded
The magnetic field gradient coils of individual separation.
Additionally, control one or more emitters 24 of such as transceiver, to utilize one or more transmitting coil array,
Such as utilize whole-body coil 26 and/or the surface coils 28 of scanning device 14, by B1Resonance excitation and manipulation radio frequency (RF) pulse are sent out
It is mapped in imaging volume 16.B1Pulse is typically the short persistent period, and when combining magnetic coil gradient, it is achieved that to magnetic altogether
The selected manipulation shaken.Such as, B1Pulse excitation hydrogen dipole photon, and magnetic field gradient is in the frequency of resonance signal and phase place
Spatial information encode.By regulation RF frequency, it is possible to excitation resonance in other dipoles, such as phosphorus, it tends to
It is gathered in the known tissue of such as bone.
Control one or more receptors 30 of such as transceiver, to receive spatially encoded magnetic altogether from imaging volume 16
Shake signal the spatially encoded magnetic resonance signal received is demodulated into MR data set.Described MR data set such as includes k
Spatial data track.In order to receive spatially encoded magnetic resonance signal, receptor 30 uses one or more receiving coil battle array
Row, the whole-body coil 26 of such as scanning device 14 and/or surface coils 28.MR data set is generally stored in caching and deposits by receptor 30
In reservoir.
The background system 58 of system 10 uses scanning device 14 that ROI is carried out imaging.Background system 58 is typically remote from scanning device
14 and include multiple module 60 (being discussed below), to use scanning device 14 to perform the imaging to ROI.Advantageously, described
Background system can characterize cardiac muscle and not selected to be affected by inaccuracy reversing time, and provides truly determining in standard scale
Amount signal quantization.
The control module 62 of background system 58 controls the overall operation of background system 58.Control module 62 uses background system
The display device 64 of 58 shows graphic user interface (GUI) suitably to the user of background system 58.Additionally, control module 62
Operator is allowed to use the user input device 66 of background system 58 to interact with GUI suitably.Such as, user can be with
GUI interacts to instruct background system 58 and coordinates the imaging to ROI.
The data acquisition module 68 of background system 58 performs the scanning of the MR to ROI.Scan for each MR, data acquisition module
Block 68, according to sweep parameter, the quantity such as cut into slices, comes control transmitter 24 and/or gradient controller 20, with at imaging volume
Image in 16 sequence.Imaging sequence limits B1Pulse and/or the sequence of magnetic field gradient, it produces space from imaging volume 16
The MR signal of coding.Additionally, data acquisition module 68 according to sweep parameter control the tuning of receptor 30 and drive circuit 36/
Demodulating control signals, to gather the MR signal of space encoding to MR data set.MR data set is typically stored within background system 58
At least one storage memorizer 70 in.
Gathering to prepare MR, ROI is positioned in imaging volume 16.Such as, patient 12 is positioned in patient support
On.Then, by surface coils 28, such as 8 or 32 channel reception head coils, it is positioned on patient 12, and patient support
ROI is moved in imaging volume 16.
The MR data set of MR diagnostic scan is redeveloped into MR image or the mapping of ROI by the reconstruction module 72 of background system 58
Figure.This includes, for each MR signal captured by MR data set, is solved space encoding spatially by magnetic field gradient
Code, to confirm from the most each pixel or the attribute of the MR signal of each area of space of voxel.The intensity of MR signal or width
Degree is typically confirmation, and other attributes about phase place, relaxation time, magnetization transfer etc. are also able to confirm that.Gathered
MR image or mapping graph be typically stored within storage memorizer 70 in.Memorizer 70 also stored for describing normal and/or various
The brain template of disease condition or atlas.
The method 100 of the enhancing of the articulated structure registration in the registration processor 74 performance objective brain of background system 58, as
Shown in fig. 2.Method 100 allows the segmenting structure in target brain to the improved registration of template brain structure.Method 100 is retouched
State segmentation and the registration utilizing hippocampus minor structure, and other anatomical structures have also been expected.
According to method illustrated 100, registration processor 74 receives MR data from data acquisition module 68.Described MR data
The MR image absorbed including target brain or other area-of-interests.Then registration processor 74 performs brain structure note 1 04,
Such as, to the segmentation of the brain structure of inside and adjacent structure in imaging region.Such as know based on local shape, adjacent structure etc.
The most also structure of labelling segmentation.Brain structure note 1 04 determines priori brain planform and attitude based on proficient annotation.Ginseng
According to Fig. 3, the hippocampus minor structure 202 of proficient annotation is superimposed in gathered target brain image.
Registration processor 74 performs overall situation brain registration 106.Registration processor 74 is primarily based on zeroth order and single order moment is counted
Calculate the target and the barycenter (CM) of reference template MRI brain image gathered.Based on this information, translate template brain image, so that
Its CM is total to position with the CM of gathered target brain image.Second, registration processor 74 calculates for template and institute based on moment
Three normal axis of orientation of the target brain image gathered, and then, rotary template brain coordinate axes so that its with gathered
The coordinate axes alignment of target brain image.3rd, registration processor 74 scales (scale) brain volume interested along three coordinate axess
Template, so that the overlapping maximization of two brain volumes；This is referred to as global registration based on isotropism moment.A reality
Executing in example, do not perform scaling, this is referred to as global registration based on anisotropy moment.In one embodiment, use such as
The registration software of Elastix performs overall situation brain registration.
In order to find volume of interest, i.e. whole hippocampus, each orthogonal direction of registration processor 74 calculation template brain
On the intersection point on border.Registration processor 74 uses template volume of interest to calculate the volume of interest of target brain.
Registration processor 74 performs hinged minor structure registration 108.Hinged minor structure registration makes to require mental skill what inside configuration existed
Hinged be registered to a width hinged image (gathered target Typical AVM) of energy fix one, such as template brain image.
With reference to Fig. 4, the target hippocampus of registration superposes with template brain image, and the part of hippocampus is applied and part is not aligned with.
In the case of the hippocampus of gathered target brain image is correctly registrated to template brain image 302, image is such as with green
(the oblique fringe area) of coloud coding.In the case of hippocampus part is not properly aligned 304, target image is such as with redness
(the horizontal stripe region) of coloud coding, and the out-of-alignment part 306 of the hippocampus structure in reference template image with
The third color (such as white (in vain)) carrys out coloud coding.By each minor structure in gyrator structure, such as, gathered
Target image in out-of-alignment hippocampus part, hinged minor structure registration 108 compensate for incorrect registration 304, thus
The overlap 306 obtaining on target and template image is made to increase.Hinged minor structure registration 108 is by the minor structure of hippocampus or part phase
Other parts for hippocampus carry out hinged to increase overlap.With reference to Fig. 5, it is each that hinged hippocampus is illustrated as according to hippocampus
Part is divided into minor structure.Described minor structure include subiculum SUB, dentate gyrus DG, entorhinal cortex EC or hippocampus angle CA1, CA2,
CA3。
In order to find the volume of interest of each minor structure, on each orthogonal direction of registration processor 74 calculation template brain
Border be intersection point.Registration processor 74 uses template subvolume of interest structural volume to calculate the subvolume of interest structure of target brain
Long-pending.
Registration processor 74 perform local cerebral registration 110 with by target brain structure registration to template brain structure.Local registration
Each voxel in target brain image is converted shape and the strength characteristic of the template brain image voxel corresponding with coupling.Office
Portion's brain registration includes such as local pixel (voxel) intensity application B-spline interpolation.In one embodiment, use such as
The registration software of Elastix or FSL FLIRT performs local cerebral registration.
With reference to Fig. 6, registration processor 74 performs hinged minor structure by first calculating brain structure link junction surface 502
Registration 108.Link junction surface is the linking point of two minor structures of the hippocampus part connecting such as misalignment and alignment.MR schemes
The physical points that is mapped in space as pixel/voxel is so that each pixel intensity level of comprising image and the physical bit of this value
Put.The physical points that junction surface between two minor structures is expressed as in space by registration processor 74.With reference to Fig. 7, in image
Two objects 602/604 represent two minor structures, the Hippocampus body 302 and 304 in such as Fig. 4.Registration processor 74 finds and connects
Conjunction portion 606, links junction surface as brain structure.Registration processor 74 by calculate have between them minimum Euclid away from
From a pair pixel/voxel (pixel/voxel carry out self-structure 602 and a pixel carrys out self-structure 604) calculate joint
Portion 606.In one embodiment, calculate one group of pixel pair, this is because there may be, there is more than a pair identical narrow spacing
From.Registration processor 74 calculates have by obtaining the distance between all combinations of pixel/voxel pair more every pair
The pixel pair of little Euclidean distance.Group is calculated from each structure 602,604 by registration processor 74 from the pixel calculated
Pixel/voxel in each mean place, to find the limit of each structure.Registration processor 74 calculates between limit
Midpoint is as junction surface 606.
Registration processor 74 applies the rotation 504 about the junction surface 606 calculated so that alignment maximizes.At hippocampus
In example, the misalignment portion of the hippocampus that registration processor 74 is rotated in gathered target brain image about junction surface 606
Divide to optimize the alignment of Hippocampus body corresponding with template brain image.Registration processor 74 first calculate gathered image with
Similarity measurement 506 between template image, to make the similarity between image maximize according to described similarity measurement.Institute
State similarity measurement can be the difference of two squares and, in normalized-cross-correlation function or mutual information metrics etc. one.Use institute
Stating similarity measurement, registration processor 74 calculates optimal transformation, the most hinged movement.In one embodiment, registration processor
74 use iterative processing to calculate optimal transformation, and wherein, registration processor 74 applies the quantitative rotation of preliminary election and calculates described phase
Measure like property, then, increase the rotation about junction surface 606 and again calculate described similarity measurement.Registration processor 74 is right
MRI bianry image is iteratively applied conversion, and it makes the overlapping maximization between object construction with MRI image.
Each module in multiple modules 60,100,110 can pass through processor executable, circuit (that is, at independent
Reason device) or combination of the two realize.Described processor executable is stored at least one of background system 58
Perform on program storage 76 and by one or more processors 78 of background system 58.As illustrated, multiple modules
60 are realized by processor executable.It should be appreciated, however, that various changes be it is envisioned that.Such as, data acquisition
Collection module 68 can be circuit.
As used in this article, memorizer include following in one or more: non-transient computer-readable medium；
Disk or other magnetic storage mediums；CD or other optical storage mediums；Random access memory (RAM), read only memory
Or other electronic storage devices or chip or operable intraconnection chipset (ROM)；Internet/intranet servers, can
To retrieve, via internet/Intranet or LAN, the instruction stored from internet/intranet servers；Deng.Additionally, such as exist
Used herein, processor include following in one or more: microprocessor, microcontroller, Graphics Processing Unit
(GPU), special IC (ASIC), FPGA etc.；Controller includes: (1) processor and memorizer, and described processor performs to deposit
The computer executable instructions of the function of controller is realized on reservoir；Or (2) simulation and/or digital hardware, it performs control
The function of device；User input device, it include following in one or more: mouse, keyboard, touch screen displays, button, open
Pass, Audio Recognition Engine etc.；Data base, it includes one or more memorizer；User's outut device, it includes that display sets
Standby, hearing devices etc.；And display apparatus, it include following in one or more: liquid crystal (LCD) display, luminous two
Pole pipe (LED) display, plasma display, the projection display, touch screen displays etc..
The present invention is described by reference to preferred embodiment.After reading and understanding detailed descriptions above, Ta Renke
To expect that some change and modifications.It is intended that and is configured to include all such changes and modifications by the present invention, as long as these become
Change and amendment falls in the range of claims or its equivalent.
Claims (20)
1. a brain registration arrangement, including:
Having the registration processor (74) of processor, it is configured to:
Brain image data is annotated；
Overall situation brain registration is used to be registrated with template image data by described brain image data；
Hinged minor structure registration is used to carry out hinged, to improve registration to the hinged minor structure of the brain structure being registered；And
Use local cerebral minor structure registration by least one brain structure registration of described brain image data to described template image number
According to corresponding brain structure.
System the most according to claim 1, wherein, described registration processor (74) is also configured to
Identify the link junction surface between described hinged minor structure.
System the most according to claim 2, wherein, described registration processor (74) is also configured to
At least one brain structure described is rotated so that overlap maximizes about described link junction surface.
4. according to the system described in any one in claim 1-3, wherein, described registration processor (74) is also configured to
Calculate at described similarity measurement between at least one brain structure and corresponding templates structure.
5. according to the system described in any one in claim 2-4, wherein, described registration processor (74) is also configured to
It is rotated in iteratively about described link junction surface in of described brain image data and described template image data
Described minor structure, and for each iterative computation similarity measurements between brain image minor structure and template image minor structure
Amount；And
Selection makes the maximized iteration of described similarity measurement.
6. according to the system described in any one in claim 1-5, wherein, described registration processor (74) is also configured to
To the application conversion of described brain image data so that between at least one brain structure described and described corresponding templates structure
Overlapping maximization.
7. according to the system described in any one in claim 2-6, wherein, described registration processor (74) is also configured to
For all pixel/voxel between described hinged minor structure to calculating Euclidean distance；
Select the pixel/voxel pair with minimum Euclideam distance；And
Calculate selected pixel/voxel between midpoint, as the described link junction surface between described minor structure.
8. according to the system described in any one in claim 1-7, wherein, described overall situation brain registration includes based on isotropism
The global registration of moment.
9. for a method for brain registration, including:
Brain image data is annotated；
Overall situation brain registration is used to be registrated with template image data by described brain image data；
Hinged minor structure registration is used to carry out hinged, to improve registration to the hinged minor structure of the brain structure being registered；And
Use local cerebral minor structure registration by least one brain structure registration of described brain image data to described template image number
According to corresponding brain structure.
Method the most according to claim 9, described hinged minor structure registration includes:
Identify the link junction surface between described hinged minor structure.
11. methods according to claim 10, described hinged minor structure registration includes:
At least one brain structure described is rotated so that overlap maximizes about described link junction surface.
12. methods according to claim 11, described hinged minor structure registration includes:
Calculate at described similarity measurement between at least one brain structure and corresponding templates structure.
13. methods according to claim 10, described hinged minor structure registration includes:
Rotate iteratively about described link junction surface in of described brain image data and described template image data
Minor structure, and for each iterative computation similarity measurement between brain image minor structure and template image minor structure；And
Selection makes the maximized iteration of described similarity measurement.
14. according to the method described in any one in claim 9-13, including:
To the application conversion of described brain image data so that weight between at least one brain structure described and described corresponding templates structure
Folded maximization.
15. methods according to claim 10, wherein, calculate described link junction surface and include:
For all pixel/voxel between described hinged minor structure to calculating Euclidean distance；
Select the pixel/voxel pair with minimum Euclideam distance；And
Calculate selected pixel/voxel between midpoint, as the described link junction surface between minor structure.
16. according to the method described in any one in claim 9-16, and wherein, described overall situation brain registration includes based on each to same
The global registration of property moment.
17. 1 kinds of non-transient computer-readable mediums, it has instruction to perform according to any one institute in claim 9-16
The method stated.
18. 1 kinds of brain registration arrangements, including:
Annotations module, it is for annotating brain image data；
Global registration module, it is used for using whole brain registration to be registrated with template image data by described brain image data；
Hinge module, it is for using hinged minor structure registration to carry out hinged to the hinged minor structure of the brain structure being registered, with
Improve registration；And
Local registration module, its for use local cerebral minor structure registration by least one brain structure of described brain image data with
The corresponding brain structure of described template image data registrates.
19. systems according to claim 18, including:
Identification module, it identifies the link junction surface between described hinged minor structure；
Rotary module, it rotates at least one brain structure described about described link junction surface, maximizes so that overlapping；
Metric module, it calculates the similarity measurement between at least one brain structure described and described corresponding templates structure；With
And
Conversion module, its to the application conversion of described brain image data so that at least one brain structure described and corresponding templates structure it
Between overlapping maximization.
20. according to the system described in any one in claim 18-19, including:
Iteration module, it rotates described brain image data and the one of described template image data iteratively about link junction surface
Minor structure in individual, and for each iterative computation similarity measurements between brain image minor structure and template image minor structure
Amount；And
Selecting module, its selection makes the maximized iteration of described similarity measurement.
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